It is necessary to compress (encode) a digital picture for promoting the efficiency of its storage and transmission. Several methods of encoding are available as prior arts such as “discrete cosine transform” (DCT) including JPEG and MPEG, and other wave-form encoding methods such as “subband”, “wavelet”, “fractal” and the like. Further, in order to remove a redundant signal between pictures, a prediction method between pictures is employed, and then the differential signal is encoded by wave-form encoding method.
According to the recent trend, the object constituting a picture are individually encoded and transmitted, for improving the coding efficiency as well as allowing reproduction of the individual objects which constitute a picture. On a reproducing side, each object is decoded, and the reproduced objects are composited into the picture for displaying. Per-object base encoding method allows the user to combine objects arbitrarily, whereby a motion picture can be re-edited with ease. Further, depending on the congestion of the communication channel, performance of a reproducing apparatus or a user's taste, even a less important object is saved from being reproduced, a motion picture can be still identified.
In order to encode a picture having an arbitrary shape (i.e., an object), an appropriate transformation method adapted to the shape is employed, such as the “shape adaptive discrete cosine transform”, or an insignificant region of the picture is padded by a predetermined method and then a conventional cosine transform (8×8) is provided, where the insignificant region is an outside of the display region of the object, and contains no pixel data for displaying an object, in other words, the region consists of insignificant sample values only. On the other hand, insignificant sample values can be found at the object boundary of a prediction region (e.g., a block consisting of 16×16 pixels) which is obtained through a motion compensation of a reference picture reproduced in the past for removing a redundant signal between pictures. This type of prediction region is firstly padded, then a the difference between the subject region and the predict region is obtained, and then, transformed and encoded. The reason why the prediction region is padded is to suppress a differential signal.
When the efficiency of encoding/decoding a digital picture is considered, how to pad the insignificant pixels is an important subject, and this influences a decoded picture quality and transmitting data quantity.
The prior art discussed above discloses the following steps: An overall picture is referenced and padded first, to prevent a prediction region from including insignificant sample values, then the prediction region is obtained by a motion compensation or other methods. How to pad the overall picture is, repeating a significant sample value on an object boundary and replacing an insignificant sample values therewith. When a sample is padded by scanning both horizontal and vertical directions, an average of both the padded values are taken. This conventional method pads the whole picture, and therefore providing a prediction region with less errors for a picture having a great motion.
However, when the whole image of a reproduced reference picture is referenced and padded, the reference picture must be entirely decoded, before padding can be started. When repetitive padding is applied, the amount of calculation increases in proportion to the picture size. In other words, this padding method requires a large amount of processing and a long delay time, and sometimes results in very large amount of calculation, for reproducing a picture.
In order to avoid calculation proportional to the picture size, a reproduced boundary region should be padded on per-region basis. This method can solve the delay time and volumes of calculation. However, since this method pads only the boundary region, the significant regions are limited within the internal region bounded by the boundary regions, and hence limiting the effect of padding. Therefore, this method cannot produce a prediction signal having less errors for a motion picture with a great motion.
Since the method of padding the overall picture results in increasing data amount, only a small advantage can be expected. In other words, an insignificant pixel has no pixel values to be encoded, and when significant pixels are encoded together with an insignificant pixel, coding efficiency is lowered. For example, when the significant pixels are all in black, the coding efficiency is lowered if insignificant pixels are in white, on the other hand, the coding efficiency is promoted if the insignificant pixels are in black. As such, a value of the insignificant pixel does not influence a quality of a reproduced picture, but influences the coding efficiency, therefore, how to deal with the insignificant pixel value should have been discussed with care.